Discrete-time Markov chain approach to contact-based disease spreading in complex networks

Gómez, Sergio; Arenas, Àlex; Borge-Holthoefer, Javier; Meloni, Sandro; Moreno, Yamir

doi:10.1209/0295-5075/89/38009

Cited by 478 publications

(427 citation statements)

References 39 publications

(60 reference statements)

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“…Values reported in the literature range between 0.1% and 50% (Ferreri et al, 2014;Pastor-Satorras and Vespignani, 2001). Following Gomez et al (2010), we chose to infect 5% (i.e., 50) of the network nodes initially. At lower values, many outbreaks may fail due to topological idiosyncrasies of the randomly chosen initial infected sites.…”

Section: Resultsmentioning

confidence: 99%

“…Gomez et al (2010) proposed a numerical method- , where C and λ are the average clustering coefficient and characteristic path length of the network, respectively, while C(p = 1) and λ(p = 1) are the equivalent values calculated for a fully rewired variant of the network. The effect peaks at around the same rewiring probability for both classes of network, but is weaker overall for REDS networks.…”

Section: Contagion On Reds Networkmentioning

confidence: 99%

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Contagion on Networks with Self-Organised Community Structure

Antonioni¹,

Bullock²,

Darabos³

et al. 2015

07/20/2015-07/24/2015

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Living systems are organised in space. This imposes constraints on both their structural form and, consequently, their dynamics. While artificial life research has demonstrated that embedding an adaptive system in space tends to have a significant impact on its behaviour, we do not yet have a full account of the relevance of spatiality to living self-organisation.Here, we extend the REDS model of spatial networks with self-organised community structure to include the "small world" effect. We demonstrate that REDS networks can become small worlds with the introduction of a small amount of random rewiring. We then explore how this rewiring influences two simple dynamic processes representing the contagious spread of infection or information.We show that epidemic outbreaks arise more easily and spread faster on REDS networks compared to standard random geometric graphs (RGGs). Outbreaks spread even faster on small world REDS networks (due to their shorter path lengths) but initially find it more difficult to establish themselves (due to their reduced community structure). Overall, we find that small world REDS networks, with their combination of short characteristic path length, positive assortativity, strong community structure and high clustering, are more susceptible to a range of contagion dynamics than RGGs, and that they offer a useful abstract model for studying dynamics on spatially organised living systems.

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Section: Resultsmentioning

confidence: 99%

Section: Contagion On Reds Networkmentioning

confidence: 99%

Contagion on Networks with Self-Organised Community Structure

Antonioni¹,

Bullock²,

Darabos³

et al. 2015

07/20/2015-07/24/2015

View full text Add to dashboard Cite

show abstract

“…The MMA method was first presented by Wang Yang in 2003 and then by S. G Mez ET [15,16] developed, which is an approximate method for analyzing dynamical processes on the network. Sahneh F D [17] established a SAIS model with an alert class using a continuous microscopic Markov chain approximation method, and the two thresholds are found; Chen Shufang [18] studied the influence of local behavior information on the rumor propagation on the network by using the micro-Markov chain approximation method, simulated it in the Small World Network, and verified the influence of the local behavior information on the rumor transmission.…”

Section: From Research Methodsmentioning

confidence: 99%

Rumor Spreading: A Survey

Jin¹,

Zhou²

2017

dtcse

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It is the key factor to restrain rumor spreading, purify the environment of network and promote network harmony that deep studying the rumor spreading. The paper first discussed the serious harmfulness of rumor spreading to society. Then, from the social media types, model research methods, model structure, research theory and whether the relationship considered the trust, the paper made the classified research and discussion of the network dissemination; finally, the paper made a prospect of the future research of rumor spreading and put forward some further research ideas.

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“…A susceptible node j will become informed at time t if it fulfills two conditions simultaneously : (1) being contacted by an informed neighbor i with probability w ij (t), and (2) being informed successfully with probability λ. The probability of node j to make a transition to the informed state by neighbors at time t is [34] …”

Section: A Theoretical Analysismentioning

confidence: 99%

Promoting information spreading by using contact memory

Gao¹,

Wang²,

Shu³

et al. 2017

EPL

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Promoting information spreading is a booming research topic in network science community. However, the exiting studies about promoting information spreading seldom took into account the human memory, which plays an important role in the spreading dynamics. In this paper we propose a non-Markovian information spreading model on complex networks, in which every informed node contacts a neighbor by using the memory of neighbor's accumulated contact numbers in the past. We systematically study the information spreading dynamics on uncorrelated configuration networks and a group of 22 real-world networks, and find an effective contact strategy of promoting information spreading, i.e., the informed nodes preferentially contact neighbors with small number of accumulated contacts. According to the effective contact strategy, the high degree nodes are more likely to be chosen as the contacted neighbors in the early stage of the spreading, while in the late stage of the dynamics, the nodes with small degrees are preferentially contacted. We also propose a mean-field theory to describe our model, which qualitatively agrees well with the stochastic simulations on both artificial and real-world networks.

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Discrete-time Markov chain approach to contact-based disease spreading in complex networks

Cited by 478 publications

References 39 publications

Contagion on Networks with Self-Organised Community Structure

Contagion on Networks with Self-Organised Community Structure

Rumor Spreading: A Survey

Promoting information spreading by using contact memory

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